Reliability Assessment Method for Simply Supported Bridge Based on Structural Health Monitoring of Frequency with Temperature and Humidity Effect Eliminated
Open accessAbstract
Structural health monitoring (SHM) has been widely used for the performance assessment of bridges, especially the methods based on dynamic characteristics. Meanwhile, bridge modal frequency is influenced significantly by environmental factors, such as temperature and humidity. Combined with SHM, a reliability assessment of bridges with the temperature and humidity effects eliminated is proposed. Firstly, the bridge deflection verification coefficient is adopted as the evaluation indicator for bridge condition, which is the ratio of deflection-measured value to deflection-calculated value. It is obtained from the relationship between verification coefficient and modal frequency through theoretical derivation. Secondly, a back propagation (BP) neural network is improved by using an artificial bee colony algorithm and employed as a surrogate model to eliminate the effect of temperature and humidity on frequency. Thirdly, a dynamic Bayesian network is applied to establish the reliability analysis model combined with the monitoring results, so that the probability distribution of bridge parameters is updated to improve the accuracy of the reliability analysis. Finally, a simply supported bridge is used as the case study, based on the proposed method in this work. The results indicate that the proposed method can eliminate the temperature and humidity effect on frequency precisely and effectively. With the effect of temperature and humidity on frequency eliminated, the bridge condition assessment can be evaluated accurately through the reliability analysis based on SHM and the dynamic Bayesian network.
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A reliability assessment approach for bridge structures is capable of eliminating temperature and humidity effects.
“This method is capable of eliminating temperature and humidity effects.”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [195]
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References 47 · Cited by 16
Research works printed but not linked: 1
- Research Institute of Highway Ministry of Transport of China. Specification for Inspection and Evaluation of Load-Bearing Capacity of Highway Bridges, 1st ed.; China Communications Press: Beijing, China, 2011. (In Chinese)
- Authors
- He, X., Tan, G., Chu, W., Zhang, S., & Wei, X.
- Affiliations
- Jilin University (CN)
- China State Construction Railway Investment & Engineering Group Co., Ltd., Beijing 100053, China
- Heilongjiang Highway Construction Center, Harbin 150081, China
- China Communications Construction Company (China) (CN)
- Corresponding author
- Tan, Guojin
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2022-08-04
- Volume
- 14
- Issue
- 15
- Pages
- 9600
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W4289861294
- Cited by
- 16
- References
- 47
- Citations by year
- 2026: 6 · 2025: 4 · 2024: 3 · 2023: 3
- FWCI
- 1.12
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (51978309, 2022-1, 2021ZDGC-5, 2020-1-3)
- Key Project of Department of Transportation of Heilongjiang Province (51978309, 2022-1, 2021ZDGC-5, 2020-1-3)
- Transportation Innovation Development Support Project of the Department of Transportation of Jilin Province (51978309, 2022-1, 2021ZDGC-5, 2020-1-3)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Engineering and Materials Analysis
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- simply supported bridges, structural health monitoring, modal frequencies, temperature and humidity effects, surrogate models, artificial bee colony algorithm, BP neural network, dynamic Bayesian networks, bridge condition assessment
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